Legal aid: the rise of the robolawyer

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Automation and machine learning will transform mundane tasks in professional services organizations.

Automation and machine learning will have as big an impact in the professional services industry as they have in manufacturing. Just as these digital technologies have revolutionized manufacturing production lines, so too they are set to overhaul mundane tasks in professional office environments.

According to Accenture, digital innovations like AI, smart robots, data science and natural language processing are improving workplace productivity in law and accountancy firms as well as management consultancies. Accenture estimates that they will reduce the workforce needed to complete a job by 4 percent per year by 2020.

Breaking down the job

Manufacturing was one of the first sectors to implement AI and automation at scale with the use of advanced robotics. Over the last few decades, manufacturers have also modularized production processes into discrete tasks, finding efficiencies along every step of the way. Today, professional services companies are bite-sizing work as well. Individual elements of a job can be automated, subcontracted or offshored – reducing the time and cost it takes to serve customers and increasing accuracy. This will allow knowledge workers to focus on higher-value tasks.

Law firms are now taking advantage of new automation technologies to perform more mundane, but still important, aspects of the job. Due diligence, client conflict checks, document review, legal research, document assembly and routine contract drafting are all areas where law firms are starting to use AI. This frees up highly qualified professionals to act as boardroom business advisors, focusing on the judgement-rich work that machines cannot do. They have more time to apply the very human qualities of abstract thinking, contextual reasoning, empathy and persuasion.

As Paul Greenwood, CIO at law firm Clifford Chance puts it, “Legal research has, until now, been very manual. It's been about getting people physically reading a lot of hard copy or electronic documents, extracting key things, writing up a summary, and presenting that to the client. This is not just expensive, but is also incredibly tedious for the people involved. AI is now able to read information far more quickly, far more efficiently, and importantly, with a high level of accuracy.”

Knowledge industries like law are, however, subject to very stringent regulation, and, given the nature of their business, required to ensure the security of sensitive customer data. So what can they do to make this process simpler?

The data journey challenge

The key lies in how law firms optimize the end-to-end journey of data through their business. Robotic process automation (RPA) tools let firms interrogate and analyze vast swathes of legal data in ways that were previously unimaginable.

These tool use deep learning algorithms. “Training data” is sent through multiple layers of densely interconnected processing nodes. Each node is programmed to apply its own “knowledge” to that data. AI adapts and “learns” throughout the process, remembering the pieces of information that contribute to a correct answer. These AI tools, trained against a firm's accumulated knowledge, are fast becoming a real source of competitive advantage.

RPA is able to analyze millions of documents in a few hours – something that would take a team of lawyers two years to do. Legal firms can also mine, analyze and present back data to clients to help them understand trends in contracts, cases and markets. But applying human judgement to the data is still key.

As Greenwood observes, “There are two measures of accuracy: recall and precision. Recall is how much of what you should be finding, do you find, and precision is how much of what you've found is relevant. What you tend to find is that machines are better at recall – they don't miss very much – but humans are much better at precision.”

Blockchain is another important area of innovation. It ensures the integrity and immutability of data by creating a globally distributed ledger system to record transactions. The use of a consensus algorithm means any changes need to be verified by the network. Its decentralized format is proving perfect for smart contracts in the cloud-enabled world.

Collaboration around data will become ever more important. Social enterprise platforms empower workers to use data insights to drive sounder business decision making. It is important to create a culture where sharing rather than owning knowledge is seen to benefit all by driving greater levels of customer focus and profitability.

With this ever-growing reliance on data to power business processes and bring insight, cyberdefense is also critical. Business ecosystems today are more complex as a result of trends such as mobile working and IoT, and data tends to be hosted in multiple data locations in the cloud and on-premise, and companies need to apply additional layers of protection according to its criticality.

At the same time, the threat landscape continually changes with Advanced Persistent Threats, Cybercrime-as-a-Service and social hacking all on the rise. Professional services firms need to be able to anticipate, detect, protect against, and respond to dynamic security threats with a multi-layered approach to security.

Real world impact already in place

These types of examples are just the vanguard of digital transformation in the professional services space. The law firms that will thrive are those that embrace AI and automation and collaborate around the data insights they uncover in a secure way. This will enable clients to benefit from faster and more accurate decision making and improved access to justice.